MATLAB的智能扫地机器人工作过程仿真

%% 环境建模（20x20网格地图）
mapSize = [20,20];
obstacleDensity = 0.2; % 障碍物密度
​
% 生成随机障碍物地图
envMap = ones(mapSize);
obstacles = randi([1,mapSize(1)], ceil(obstacleDensity*prod(mapSize)), 2);
envMap(sub2ind(size(envMap), obstacles(:,1), obstacles(:,2))) = 0;
​
%% 机器人参数设置
robot = struct(...
    'pos', [2,2], ...      % 初始位置
    'dir', 0, ...          % 初始方向(0:上,1:右,2:下,3:左)
    'speed', 0.5, ...      % 移动速度(m/s)
    'sensorRange', 3 ...   % 传感器探测范围
);
​
%% 路径规划（改进内螺旋算法）
function path = spiralPath(map, startPos)
    [rows,cols] = size(map);
    path = [];
    x = startPos(1); y = startPos(2);
    dir = [0,1;1,0;0,-1;-1,0]; % 右下左上
    d = 0; step = 1; turns = 0;
    
    while true
        for i = 1:2
            for j = 1:step
                if x<1 || x>rows || y<1 || y>cols || map(x,y)==0
                    return;
                end
                path = [path; x,y];
                map(x,y) = 0; % 标记已清扫
                x = x + dir(d+1,1);
                y = y + dir(d+1,2);
            end
            d = mod(d,4)+1;
        end
        step = step + 1;
    end
end
​
%% 避障算法（动态A*算法）
function newPath = dynamicAStar(start, goal, envMap)
    % 实现A*算法，考虑动态障碍物
    % 省略具体实现（需结合实时传感器数据）
end
​
%% 运动控制仿真
dt = 0.1; % 时间步长
totalSteps = 500;
trajectory = zeros(totalSteps,2);
​
for t = 1:totalSteps
    % 传感器扫描（模拟激光雷达）
    scanData = simulateLidar(robot.pos, robot.sensorRange, envMap);
    
    % 动态路径规划
    if isempty(scanData.obstacles)
        newPath = spiralPath(envMap, robot.pos);
    else
        newPath = dynamicAStar(robot.pos, [20,20], envMap);
    end
    
    % 运动控制
    robot = moveRobot(robot, newPath(1,:), dt);
    trajectory(t,:) = robot.pos;
    
    % 更新环境状态
    envMap(robot.pos(1), robot.pos(2)) = 0.5; % 标记清扫区域
end
​
%% 可视化
figure;
hold on;
imagesc(envMap);
colormap([1 1 1; 0 0 0; 0.5 0.5 0.5]); % 白色-空闲，黑色-障碍，灰色-清扫区
plot(trajectory(:,2), trajectory(:,1), 'r-o', 'LineWidth',2);
plot(robot.pos(2), robot.pos(1), 'bo', 'MarkerSize',10);
title('扫地机器人工作轨迹');
xlabel('X轴'); ylabel('Y轴');
axis equal;
hold off;

function path = improvedSpiral(map, startPos)
    [rows,cols] = size(map);
    path = [];
    directions = [0,1;1,0;0,-1;-1,0]; % 右下左上
    d = 0; step = 1; layer = 0;
    
    while true
        for i = 1:2
            for j = 1:step
                x = startPos(1) + d*layer*(i==1 ? 1 : -1);
                y = startPos(2) + d*layer*(i==2 ? 1 : -1);
                if x<1 || x>rows || y<1 || y>cols || map(x,y)==0
                    return;
                end
                path = [path; x,y];
                map(x,y) = 0;
            end
            d = mod(d,4)+1;
        end
        step = step + 1;
        layer = layer + 0.5; % 螺旋膨胀系数
    end
end

function newDir = obstacleAvoid(robot, envMap)
    % 基于势场法的避障
    [x,y] = meshgrid(-2:2, -2:2);
    x = x(:); y = y(:);
    valid = (x>=1) & (x<=size(envMap,1)) & (y>=1) & (y<=size(envMap,2));
    x = x(valid); y = y(valid);
    
    % 计算势场力
    dist = sqrt((x-robot.pos(1)).^2 + (y-robot.pos(2)).^2);
    F_rep = 1000 ./ (dist.^2 + 1e-6); % 斥力场
    F_att = -50 * (robot.pos - [13,13]); % 目标引力
    
    % 合成运动方向
    F = F_rep + F_att;
    [~,idx] = max(F);
    newDir = [x(idx)-robot.pos(1), y(idx)-robot.pos(2)];
    newDir = newDir / norm(newDir);
end

% 自动分区清扫
regions = detectRooms(envMap);
for i = 1:numel(regions)
    spiralPath(regions{i}, [2,2]);
end

% ROS消息发布
rosinit('192.168.1.100');
pub = rospublisher('/robot1/cmd_vel','geometry_msgs/Twist');

% 卡尔曼滤波跟踪
[x_pred, P_pred] = predict(kalmanFilter, sensorData);
[x_upd, P_upd] = correct(kalmanFilter, x_pred, P_pred, sensorData);

% 无人机+扫地机器人协同
[X,Y,Z] = ndgrid(1:0.5:20, 1:0.5:20, 1:2);

% 语音指令识别
speech = audiorecorder(8000,16,1);
recordblocking(speech,2);
command = recognizeSpeech(speech);

% 电池状态监控
battLevel = 100 - 0.1*pathLength;
if battLevel < 20
    dockingStation();
end